This paper presents a novel Cobotic system with differential CVT. The new system is significantly cheaper, simpler to control and more efficient than Cobots with S-CVTs. Both path-guidance and power-assist functions can be simply realized with the new system. Basic structures, kinematic and dynamic models, as well as control algorithms, which are essential for design, control synthesis and control of the system, are briefly presented in the paper.

The contributions to this issue aim to provide robotics and, in general, the automatic control community with results of research and applications focused on the cost-effectiveness of automation systems.

Low Cost Automation or Cost Effective Automation promotes cost oriented reference architectures and development approaches that properly integrate human skill and technical solutions, includes decentralized process control strategies, addresses automation integrated with information processing, as well as automation of non-sophisticated and easily handled operations for production maintenance.

Low Cost Automation is not an oxymoron like military intelligence or jumbo shrimps. It opposes the rising cost of sophisticated automation and propagates the use of innovative and intelligent solutions at an affordable cost. The concept can be regarded as a collection of methodologies aiming at exploiting tolerance of imprecision or uncertainties to achieve tractability, robustness and, in the end, low cost solutions. Mathematically, elegant designs of automation systems are often not feasible because of neglecting real world problems, i.e. they are failure-prone and therefore often very expensive for their users.

Low Cost Automation does not mean basic or poor performance control. The design of automation systems considers their life cycle with respect to their costs. For example, machine vision, despite in some cases costly components, properly applied can reduce the overall cost. It is used to guide field robots, identifying and assembling parts, and to sort out agricultural products.

Execution monitoring is a proven tool for securing program execution and to enforce safety properties on applets and mobile code, in particular. Inlining monitoring tools perform their task by inserting certain run-time checks into the monitored application before executing it. For efficiency reasons, they attempt to insert as few checks as possible using techniques ranging from simple ad hoc optimizations to theorem proving. Partial evaluation is a powerful tool for specifying and implementing program transformations. The present work demonstrates that standard partial evaluation techniques are sufficient to transform an interpreter equipped with monitoring code into a non-standard compiler. This compiler generates application code, which contains the inlined monitoring code. If the monitor is enforcing a security policy, then the result is a secured application code. If the policy is defined using a security automaton, then the transformation can elide many run-time checks by using abstract interpretation. Our approach relies on proper staging of the monitoring interpreter. The transformation runs in linear time, produces code linear in the size of the original program, and is guaranteed not to duplicate incoming code.

Cyclone is a type-safe programming language that provides explicit run-time code generation. The Cyclone compiler uses a template-based strategy for run-time code generation in which pre-compiled code fragments are stitched together at run time. This strategy keeps the cost of code generation low, but it requires that optimizations, such as register allocation and code motion, are applied to templates at compile time. This paper describes a principled approach to implementing such optimizations. In particular, we generalize standard flow-graph intermediate representations to support templates, define a mapping from (a subset of) Cyclone to this representation, and describe a dataflow-analysis framework that supports standard optimizations across template boundaries.

This work deals with the real-time robot control implementation. In this paper, an algorithm for solving Inverse Dynamic Problem based on the Gibbs-Appell equations is proposed and verified. It is developed using mainly vectorial variables, and the equations are expressed in a recursive form, it has a computational complexity of O(n). This algorithm will be compared with one based on Newton-Euler equations of motion, formulated in a similar way, and using mainly vectors in their recursive formulation. This algorithm was implemented in an industrial PUMA robot. For the robot control a new and open architecture based on PC had been implemented. The architecture used has two main advantages. First it provides a total open control architecture, and second it is not expensive. Because the controller is based on PC, any control technique can be programmed and implemented, and in this way the PUMA can work on high level tasks, such as automatic trajectory generation, task planning, control by artificial vision, etc.

This paper considers human-centered and socially appropriate robots as well as automation systems within the context of their cost-effectiveness. Usually, the objection of system designers is that approaches for human-centered and socio-technical design result in systems that are more expensive than those made by traditional methods, and are therefore not truly affordable, in particular for small and medium sized enterprises (SMEs). This widespread opinion is challenged in the paper by some arguments supporting the forecast that human-centered and socio-technical design will soon become justifiable in tangible (economic) as well as intangible benefits for all involved partners, including society at large.

Representing defeasibility is an important issue in common sense reasoning. In reasoning about action and change, this issue becomes more difficult because domain and action related defeasible information may conflict with general inertia rules. Furthermore, different types of defeasible information may also interfere with each other during the reasoning. In this paper, we develop a prioritized logic programming approach to handle defeasibilities in reasoning about action. In particular, we propose three action languages ${\cal AT}^{0}$, ${\cal AT}^{1}$, and ${\cal AT}^{2}$ which handle three types of defeasibilities in action domains named defeasible constraints, defeasible observations and actions with defeasible and abnormal effects respectively. Each language with a higher superscript can be viewed as an extension of the language with a lower superscript. These action languages inherit the simple syntax of ${\cal A}$ language but their semantics is developed in terms of transition systems where transition functions are defined based on prioritized logic programs. By illustrating various examples, we show that our approach eventually provides a powerful mechanism to handle various defeasibilities in temporal prediction and postdiction. We also investigate semantic properties of these three action languages and characterize classes of action domains that present more desirable solutions in reasoning about action within the underlying action languages.

Quay cranes are particular transportation devices for which operation's safety and CRAMP parameters (Cost, Reliability, Availability, Maintainability, and Productivity) should be fulfilled with regard to a harbor maintenance strategy. The maintenance process is first considered within a holistic modeling framework in order to cope with the current practices of treating strategic, operational and engineering maintenance issues independently without taking into account their interactions within an entire Enterprise System. Proactive maintenance is then highlighted as a new model aiming to globally optimize the components operation parameters throughout three interacting prognosis, diagnosis and monitoring processes. Technical issues related to Intelligent Maintenance System are finally proposed in order to support proactive maintenance operations at the enterprise field level and applied to quay cranes in a particular site within the frame of the European Eureka ‘Robcrane' project.

In this paper distributed architectures for autonomous vehicles are addressed, with a special emphasis on its real-time control requirements. The interconnection of the distributed intelligent subsystems is a key factor in the overall performance of the system. To better understand the interconnection requirements, the main techniques and modules of a global navigation system are described. A special focus on fieldbuses properties and major characteristics is made in order to point out some potentialities, which make them attractive in autonomous vehicles real-time applications, either in terms of reliability as in terms of real-time restrictions.

When writing a program generator requires considerable intellectual effort, it is valuable to amortize that effort by using the generator to build more than one application. When a program generator serves multiple clients, however, the implementor must address pragmatic questions that implementors of single-use program generators can ignore. In how many languages should generated code be written? How should code be packaged? What should the interfaces to the client code look like? How should a user control variations? This paper elaborates on these questions by means of case studies of the New Jersey Machine-Code Toolkit, the $\lambda$-RTL Translator, and the ASDL program generator. It is hoped that the paper will stimulate the development of better techniques. Most urgently needed are a standard way to support multiple target languages and a simple, clear way to control interfaces to generated code.

This paper describes learning in a compiler for algorithms solving classes of the logic minimization problem MINSAT, where the underlying propositional formula is in conjunctive normal form (CNF) and where costs are associated with the True/False values of the variables. Each class consists of all instances that may be derived from a given propositional formula and costs for True/False values by fixing or deleting variables, and by deleting clauses. The learning step begins once the compiler has constructed a solution algorithm for a given class. The step applies that algorithm to comparatively few instances of the class, analyses the performance of the algorithm on these instances, and modifies the underlying propositional formula, with the goal that the algorithm will perform much better on all instances of the class.

Inlining and specialization appear in various forms throughout the implementation of modern programming languages. From mere compiler optimizations to sophisticated techniques in partial evaluation, they are omnipresent, yet each application is treated differently. This paper is an attempt at uncovering the relations between inlining (as done in production compilers) and staged computation (as done in partial evaluators) in the hope of bringing together the research advances in both fields. Using a two-level lambda calculus as the intermediate language, we show how to model inlining as a staged computation while avoiding unnecessary code duplication. The new framework allows us to define inlining annotations formally and to reason about their interactions with module code. In fact, we present a cross-module inlining algorithm that inlines all functions marked inlinable, even in the presence of ML-style parameterized modules.

An open ended list is a well known data structure in Prolog programs. It is frequently used to represent a value changing over time, while this value is referred to from several places in the data structure of the application. A weak point in this technique is that the time complexity is linear in the number of updates to the value represented by the open ended list. In this programming pearl we present a variant of the open ended list, namely an open ended tree, with an update and access time complexity logarithmic in the number of updates to the value.

With the fast development of the control theory and engineering, robotics and artificial intelligence have become the focus in the field of intelligent systems. But research in this field is based on a series of experiments and requires various robot platforms which are often unaffordable by the universities in developing countries. The intention of this paper is to present the idea of applying innovative control education and building a laboratory using low cost equipments. In this paper the architecture and control system of a new kind of low cost intelligent robot, “Ability Storm”, is introduced. It not only shows the technical aspect, but also illustrates the related applications in control education. The versatility and effectiveness of this affordable intelligent robot platform are demonstrated through a number of experiments, including both basic laboratory experiments and other innovative project-oriented design, such as robot fire fighting, which clearly show the practicality and robustness of this cost-effective robot platform.

Low cost automation often requires accurate positioning. This happens whenever a vehicle or robotic manipulator is used to move materials, parts or minerals on the factory floor or outdoors. In last few years, such vehicles and devices are mostly autonomous. This paper presents the method of sensor fusion based on the Adaptive Fuzzy Kalman Filtering. This method has been applied to fuse position signals from the Global Positioning System (GPS) and Inertial Navigation System (INS) for the autonomous mobile vehicles. The presented method has been validated in 3-D environment and is of particular importance for guidance, navigation, and control of mobile, autonomous vehicles. The Extended Kalman Filter (EKF) and the noise characteristic have been modified using the Fuzzy Logic Adaptive System and compared with the performance of regular EKF. It has been demonstrated that the Fuzzy Adaptive Kalman Filter gives better results (more accurate) than the EKF. The presented method is suitable for real-time control and is relatively inexpensive. Also, it applies to fusion process with sensors different than INS or GPS.